Abstract
CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart) are widespread security measures on the World Wide Web that prevent automated programs from abusing online services. CAPTCHAs are designed to be easy for humans but hard for machines. Academic research into CAPTCHAs takes the form of a friendly ‘arms race’, with some researchers acting as ‘malicious users’ that try to attack and defeat the latest CAPTCHA systems automatically. Defeating a CAPTCHA requires two procedures: segmentation and recognition. Recent research shows that the problem of segmentation is much harder than recognition. The efforts to break the CAPTCHA determine its strength & thus in turn help the researcher to build stronger CAPTCHA. In order to test the strength of a particular CAPTCHA, in this paper, we have developed a universal algorithm that measures one of the parameters to measure strength of CAPTCHA. The proposed algorithm can adapt to various cases for segmenting characters from CAPTCHA image. The said algorithm is inspired from projection value of characters, concept of snake game and typical patterns of touching the characters. Experimental results prove that the proposed algorithm has improved correct segmentation rates giving accuracy of 85%.
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Chandavale, A.A., Sapkal, A. (2012). A New Approach towards Segmentation for Breaking CAPTCHA. In: Thampi, S.M., Zomaya, A.Y., Strufe, T., Alcaraz Calero, J.M., Thomas, T. (eds) Recent Trends in Computer Networks and Distributed Systems Security. SNDS 2012. Communications in Computer and Information Science, vol 335. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34135-9_33
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DOI: https://doi.org/10.1007/978-3-642-34135-9_33
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